Our invention is useful in many civilian and military applications. Known usages range from search-and-rescue situations requiring parachute or other aerial drops of emergency supplies, and police operations needing prompt delivery of nonlethal weapons such as large nets or tasers (from helicopters or drones), and through paratrooper tactical planning, to attack devices—e.g. guided missiles or munitions.
In one such known application, ideally but not exclusively for airborne vehicles, the angle of the velocity vector relative to the platform (vehicle) centerline is used to align the platform to its own motion. Such alignment has particular utility in connection with certain kinds of very well-known military attack hardware.
Most such hardware already has an attitude-correction autopilot, in which case the misalignment angle can simply be is provided as an input to that autopilot—which then effectuates the desired correction. The purpose of such alignment is closely related to the specific type of military hardware involved. Generally such hardware is of so-called “bunker busting” types, which are intended to penetrate hardened opponent installations.
If the tip of a bunker buster is pointed directly forward, penetration typically is much deeper than when the tip is oriented even slightly sideways. In the latter case, the vehicle behaves somewhat more like a blunt object, delivering a blow that may be dissipated in surface shattering, rather than yielding the desired deep penetration.
In a second such known optical-flow strategy, more broadly useful than the military application just outlined, a destination (e.g. impact point) defined in collected images is provided to guidance algorithms for terminal homing accuracy improvement. The analysis in this case is intended simply to greatly refine precision and accuracy in reaching the destination.
Even though such systems can sometimes or even often work very well, they are overall unsatisfactory. The reason is that heretofore a starting point for such guidance and control applications generally has been data derived from “navigation”—specifically meaning determining present location, through use of certain kinds of equipment.
Such equipment can include a GPS system, or an inertial system (most typically mechanical or optical gyroscopes), or in earlier eras sightings of the sun and other celestial objects using transits or more-modern equivalents. Navigation is limited, as ever it has been, to finding of a current location—leaving it to people and their artificial aids to divine where to go next, and how to get there.
Reliance on navigation is often problematic because suitable navigation equipment is often unavailable or functionally inadequate—and for some purposes can be overly bulky, heavy or expensive—or combinations of these.
For example traditional navigation relies upon tedious manual methods that are far too slow for modern automated terminal-approach situations. Current-day navigation methods such as global positioning systems, though much faster, may yet fail to be suitable for accurate homing.
As a further example, a GPS-guided vehicle can have a bias in its navigation solution, and this can throw the guidance off severely. In areas where GPS functionality is denied or degraded, operators may have a photographic image but not full coordinates of the desired destination point. (Present technology fails to fully exploit availability of such an image, in producing accurate guidance solutions without aid by navigation.)
A problem with some such approaches is that angular-attitude accuracy is often insufficient to meet alignment requirements for penetrating-munition alignment. Another method is to use accelerometer data from an INS/GPS system. Having the autopilot command the munition to zero acceleration drives the so-called “angle of attack” to zero; however, that is an aerodynamic angle of attack, not the angle between the inertial velocity and the munition. A moderate crosswind puts the munition into an out-of-specification condition.
Certain previously known forms of optical-flow analysis have been used for vehicle guidance and control, particularly in ground vehicles. In that context, the optical-flow variant known as “structure through flow” has been applied to generate three-dimensional (“3D”) maps of the environment of a vehicle.
Then when the environment is sufficiently mapped, ground-vehicle guidance computers can make intelligent steering decisions based on such mappings. Use of optical-flow mapping in ground vehicles, in this way, may be regarded as very loosely analogous to the basing of other kinds of optical-flow procedures upon navigation as mentioned above. Accordingly these usages—which are not the present invention—require navigation or analogous external information sources, and as noted above these are often infeasible, inconvenient or unavailable.
Thus in many situations there is a profound need for faster and more precise guidance and control. Although earlier efforts toward solving this need have been praiseworthy, the prior art has left considerable room for refinement.